Build on Radiens
Explore data interactively in the GUI — then run the same workflow at scale in Python. GUI↔API parity means what you discover by hand becomes a batch pipeline without rewriting anything.
Explore to scale
The same operations — GUI or Python, identical outputsThe hardest transition in data-rich science is moving from a small slice of data to the whole archive. Radiens is built for exactly that round trip: explore a feature interactively in Videre, then automate the same discovery across thousands of sessions in RadiensPy — no reimplementation required.
Explore in the GUI
Use Videre to find features and effects quickly — spike sorting, LFP/spectral analysis, signal metrics — without writing a line of code.
Scale in Python
Translate the same workflow to RadiensPy and run it unattended across hundreds of sessions. The algorithms and outputs are identical — not reimplemented.
Less code, better science
Thin, high-level scripts mean fewer bugs and easier maintenance. Heavy computation runs in the compiled back end — short readable scripts, full performance.
GUI ↔ API parity
Every operation in Videre is a Python call with identical outputsRadiensPy is not a thin wrapper — it shares the same computational core as Videre. Signal metrics, sorting results, session data: the GUI and the API always agree. Export any GUI workflow as an executable script and run it immediately.
Workflow export
Click "Export Workflow" in any Videre module to receive an executable .py file — every step translated, nothing to reconstruct by hand.
Identical outputs
The GUI and API share a computational core. Signal metrics, sorting results, session grades — always the same.
No feature gaps
Every Videre capability is available as a Python call. There are no "GUI-only" operations.
Quality-aware pipelines in code
Access the full quality metadata chain from PythonBuild pipelines that skip bad channels, weight results by signal quality, and aggregate provenance automatically. Allego quality metrics, Videre sorting results, and per-session signal grades are all available as Python objects.
Acquisition quality metrics
Per-channel SNR, impedance history, spike yield, and noise floor from Allego — as Python objects ready for filtering and aggregation.
Sorting results and unit data
Load spike-sorting results, cluster quality scores, and unit tracking data without format conversion.
Batch across sessions
Run the same quality-gated pipeline across an entire archive. Aggregate results in pandas, export to NWB.
Built for scientific Python
A first-class package — installable, typed, documented, and usable wherever Python runs.
Get started
Installation, supported Python versions, and the API reference are in the RadiensPy documentation.
Full type annotations
Complete type hints. IDE autocompletion, inline docs, and static analysis across every API surface.
Jupyter-native
Interactive widgets, inline visualizations, and rich HTML outputs for notebook-first workflows.
Notebook library
Downloadable example notebooks for acute recordings, chronic studies, batch processing, and NWB export.
API reference
Conceptual guides, tutorials, and runnable examples for every module in the documentation site.
Semantic versioning
Stable public API with deprecation notices. Analysis scripts survive Radiens updates without changes.
API clients
RadiensPy has one client per Radiens app.
AllegoClient
Control streaming and recording, read live signals and signal-quality metrics, configure filters, and run spike sorting, stimulation, and hardware diagnostics.
VidereClient
Link recorded files, read signals, spikes, and units, compute signal-quality and spectral metrics, and filter, re-reference, downsample, and slice datasets with reusable protocols.
What's coming to RadiensPy
Two capabilities are in development and will extend RadiensPy when they ship. Neither is available today.
- —Archive triage — session-grade queries and dataset-level quality metadata at scale (coming soon)
- —Radiens-4 real-time API — live file tailing and live PSTH during active Allego sessions (in development)
Developers — FAQ
How do I install RadiensPy?
Installation steps and supported Python versions are in the [RadiensPy documentation](https://neuronexus.github.io/radiens-core-python/latest/). RadiensPy requires Videre, Allego, or Radiens Compute installed.
Does RadiensPy have full parity with the Radiens apps?
Yes — RadiensPy has full GUI-to-API parity: every operation available in Allego and Videre is available as a Python call, so anything you can do by hand you can script.
What can I automate with RadiensPy?
Acquisition control, spike sorting, LFP and spectral analysis, curation, and export — the same operations the desktop apps expose, composed into reproducible pipelines and agent workflows.
Can I run Radiens headless or in a notebook?
Yes. RadiensPy is notebook-first and supports headless mode with no display server required, so it fits scripted and remote HPC workflows.